Module 9 of 10

Optimization & Experimentation

Fine-tune prompts for production

🎯 Control Output Length

Tokens = cost. Be explicit about desired length to avoid paying for unnecessary output.

❌ Vague:

"Write about AI"

Could generate 10 words or 1000 words!

✅ Specific:

"Write a 2-paragraph (~100 word) summary of AI"

Clear expectations, controlled cost

💡 Length Specifications:

Word count: '~100 words'
Sentences: '3-5 sentences'
Bullets: '5 bullet points'
Paragraphs: '2 paragraphs'

🔧 Use Variables for Dynamic Prompts

Create template prompts with variables you can swap out. Perfect for production systems!

Template Example:

Prompt Template:

"Generate a {{ TONE }} email to {{ RECIPIENT }} about {{ TOPIC }}. Keep it under {{ WORD_COUNT }} words."

Example Usage:

TONE = "friendly"
RECIPIENT = "customer"
TOPIC = "order delay"
WORD_COUNT = 100

Benefits:

Reusable templates across your app
Easy A/B testing of variations
Consistent formatting
Faster development

🧪 Experiment with Output Formats

The same content, different formats. Test to see what works best:

Bullet Points

Easy to scan

1.

Numbered Lists

Shows sequence

Tables

Compare data

{}

JSON

Machine-readable

#

Markdown

Rich formatting

</>

Code Blocks

Technical content

📊 A/B Test Your Prompts

Just like UI design, test different prompt variations to see what gives better results.

Test Variables:

Wording: 'analyze' vs 'examine'
Tone: formal vs casual
Length: short vs detailed
Examples: 2 vs 6 examples
Order: context first vs task first
Format: JSON vs bullets

📈 Measure Success:

Track: accuracy, response time, user satisfaction, cost per request

✅ Optimization Checklist

Specify exact output length to control tokens

Use template variables for reusability

Test multiple output formats

A/B test prompt variations

Measure accuracy vs cost trade-offs

Cache common responses when possible

Use lower temp (0.3) for consistency

Set max_tokens limit to prevent runaway costs

Document what works for future reference

🎓 Key Takeaways

Always specify output length to control token usage and cost

Use variables/templates for reusable, scalable prompts

Experiment with different output formats

A/B test prompt variations to optimize performance

Track metrics: accuracy, speed, cost, user satisfaction

Set max_tokens limit to prevent runaway costs

Document successful patterns for team reuse

Production prompts need optimization, not just functionality

Module 9 of 10 Complete